{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a3435","dataset_id":"ds006065","associated_paper_doi":null,"authors":["James Kragel","Joel Voss"],"bids_version":"1.8","contact_info":["James Kragel"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds006065.v1.0.0","datatypes":["ieeg"],"demographics":{"subjects_count":7,"ages":[],"age_min":null,"age_max":null,"age_mean":null,"species":null,"sex_distribution":null,"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds006065","osf_url":null,"github_url":null,"paper_url":null},"funding":["This research was funded by the National Institute Of Neurological Disorders and Stroke under Award Number R01NS113804"],"ingestion_fingerprint":"7406564d5ea54c221fb310ddccd49c844aaa4f75f620ec9792ce0ac7f52616c4","license":"CC0","n_contributing_labs":null,"name":"TSS_iEEG","readme":"# iEEG Dataset: Theta-synchronized Stimulation of Human Hippocampal Networks\n## Information\nThis folder contains intracranial EEG (iEEG) data from **7 participants** undergoing closed-loop stimulation as part of a study on hippocampal network connectivity, as used in the following publication:\n**Kragel et al., 2025, Nature Communications:**\n*“Closed-loop control of theta oscillations enhances human hippocampal network connectivity”*\nFor questions or further information, contact:\n- **James Kragel:** [jkragel@uchicago.edu](mailto:jkragel@uchicago.edu)\n- **Joel Voss:** [joelvoss@uchicago.edu](mailto:joelvoss@uchicago.edu)\n---\n## License\nThis dataset is made available under the **Public Domain Dedication and License v1.0**.\nFull text: [http://www.opendatacommons.org/licenses/pddl/1.0](http://www.opendatacommons.org/licenses/pddl/1.0)\n---\n## Dataset and Protocol\nThe data are organized according to the **Brain Imaging Data Structure (BIDS)** iEEG specification, a community-driven standard for organizing neurophysiology data along with its metadata.\n### Structure\nEach subject folder contains the raw iEEG data for that subject, segmented into different periods of the stimulation protocol:\n- **Pre-stimulation evoked potentials**\n- **Post-stimulation evoked potentials**\n- **Pre-stimulation rest**\n- **Post-stimulation rest**\n- **Closed-loop stimulation**\n- **Control stimulation**\n---\n## Raw Data\nThe raw data are stored in **BrainVision format** (`vhdr`, `vmrk`, and `eeg` files). You can read these files into memory using the following tools:\n- **MATLAB:** [FieldTrip toolbox](https://www.fieldtriptoolbox.org/getting_started/eeg/brainvision/)\n- **Python:** [`pybv` package](https://github.com/bids-standard/pybv)\n### Electrode Coordinates\nElectrode coordinates are provided in **MNI space**, registered to the **MNI152 2009c asymmetrical template**.","recording_modality":["ieeg"],"senior_author":"Joel Voss","sessions":[],"size_bytes":10343281171,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["cl","clcontrol","epcontrolpost","epcontrolpre","eppost","eppre","restcontrolpost","restcontrolpre","restpost","restpre"],"timestamps":{"digested_at":"2026-04-22T12:29:04.994121+00:00","dataset_created_at":"2025-03-27T15:20:02.439Z","dataset_modified_at":"2025-03-29T20:06:49.000Z"},"total_files":45,"storage":{"backend":"s3","base":"s3://openneuro.org/ds006065","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.tsv"]},"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"4d64c471472f8621","model":"openai/gpt-5.2","tagged_at":"2026-04-07T09:32:40.872789+00:00"},"tags":{"pathology":["Surgery"],"modality":["Other"],"type":["Clinical/Intervention"],"confidence":{"pathology":0.6,"modality":0.7,"type":0.8},"reasoning":{"few_shot_analysis":"Closest few-shot convention match is the Parkinson’s cross-modal oddball dataset labeled Type=Clinical/Intervention because the primary purpose is a clinically-relevant mechanistic/biomarker question in a patient cohort and not a classic cognitive task. Similarly, this dataset centers on a neuromodulation protocol (\"closed-loop stimulation\" / \"control stimulation\") and evoked potentials/rest segments, which aligns with labeling the study purpose as Clinical/Intervention rather than (e.g.) Attention/Memory. For Modality, none of the few-shots cover direct intracranial electrical stimulation; when the input is not a standard sensory channel (auditory/visual/tactile) and is instead a device-based perturbation, the few-shot style implies using Modality=Other. For Pathology, the epilepsy few-shot shows that when epilepsy is explicitly stated, Pathology=Epilepsy; here no diagnosis is explicitly stated, so we should not infer Epilepsy, and instead use a more general clinical recruitment label (Surgery) or Unknown.","metadata_analysis":"Key metadata facts:\n1) Population/protocol: \"intracranial EEG (iEEG) data from **7 participants** undergoing closed-loop stimulation\".\n2) Intervention framing: \"Theta-synchronized Stimulation of Human Hippocampal Networks\" and the cited paper title \"Closed-loop control of theta oscillations enhances human hippocampal network connectivity\".\n3) Recording segments/tasks indicate stimulation + rest/EPs rather than a cognitive paradigm: dataset contains \"Pre-stimulation evoked potentials\", \"Post-stimulation evoked potentials\", \"Pre-stimulation rest\", \"Post-stimulation rest\", \"Closed-loop stimulation\", \"Control stimulation\"; and tasks list includes \"cl\", \"clcontrol\", multiple \"rest*\" and \"ep*\" entries.\n4) Clinical implantation is implied by \"intracranial EEG (iEEG)\" but no explicit diagnosis (e.g., epilepsy) is stated anywhere in the provided metadata.","paper_abstract_analysis":"No useful paper information. (Only the paper title/citation is provided; no abstract text included.)","evidence_alignment_check":"Pathology:\n- Metadata says: \"intracranial EEG (iEEG)\" and participants are \"undergoing closed-loop stimulation\" (clinical/implanted context implied), but metadata does NOT name a diagnosis.\n- Few-shot pattern suggests: if epilepsy were stated, use Epilepsy (as in the pediatric epilepsy example); if clinical intervention/stimulation without explicit diagnosis, use a broad clinical recruitment label.\n- Alignment: PARTIAL. Both imply a clinical context, but diagnosis is missing.\n- Resolution: choose Surgery (implant-based iEEG/stimulation cohort) rather than Epilepsy because explicit diagnosis is absent (metadata facts override any inferred epilepsy pattern).\n\nModality:\n- Metadata says: stimulation protocol and segments include \"Closed-loop stimulation\" / \"Control stimulation\" plus rest/evoked potentials; no auditory/visual/tactile stimulus described.\n- Few-shot pattern suggests: when dominant input is not a standard sensory channel, label Modality=Other.\n- Alignment: ALIGN.\n\nType:\n- Metadata says: intervention focus \"Theta-synchronized Stimulation\" / \"Closed-loop control of theta oscillations enhances... connectivity\" and protocol structure is stimulation/rest/evoked potentials.\n- Few-shot pattern suggests: intervention-centric datasets map to Type=Clinical/Intervention (e.g., PD cohort mechanistic/biomarker-focused task battery labeled Clinical/Intervention).\n- Alignment: ALIGN.","decision_summary":"Top-2 candidates and selection:\n\nPathology:\n1) Surgery — Evidence: (a) \"intracranial EEG (iEEG)\" implies implanted electrodes; (b) participants \"undergoing closed-loop stimulation\"; (c) protocol includes stimulation/evoked potentials typical of implanted clinical cohorts.\n2) Unknown — Evidence: no explicit diagnosis or surgical indication is directly stated.\nHead-to-head: Surgery is stronger because iEEG + stimulation strongly implies an implanted/surgical patient cohort, even though diagnosis is unspecified. Confidence limited because this remains an inference (no explicit 'epilepsy'/'surgery' recruitment statement).\n\nModality:\n1) Other — Evidence: \"Closed-loop stimulation\" and \"Control stimulation\" indicate electrical stimulation rather than sensory stimuli.\n2) Resting State — Evidence: includes \"Pre-stimulation rest\" and \"Post-stimulation rest\".\nHead-to-head: Other wins because the dominant experimental manipulation/input is stimulation (non-sensory), with rest as a segment type within that protocol.\n\nType:\n1) Clinical/Intervention — Evidence: (a) \"Theta-synchronized Stimulation\"; (b) \"Closed-loop control... enhances... connectivity\"; (c) task structure is stimulation + EPs/rest, consistent with an intervention/neurostimulation study.\n2) Resting-state — Evidence: multiple rest periods exist (\"restpre\", \"restpost\").\nHead-to-head: Clinical/Intervention wins because the study purpose centers on closed-loop stimulation effects, with rest/EPs as measurement components. Confidence is higher due to multiple explicit quotes about stimulation/intervention focus."}},"computed_title":"TSS_iEEG","nchans_counts":[{"val":168,"count":15},{"val":175,"count":10},{"val":68,"count":5},{"val":43,"count":5},{"val":82,"count":5},{"val":181,"count":5}],"sfreq_counts":[{"val":500.0,"count":45}],"stats_computed_at":"2026-04-22T23:16:00.311289+00:00","total_duration_s":38517.088,"canonical_name":null,"name_confidence":0.74,"name_meta":{"suggested_at":"2026-04-14T10:18:35.343Z","model":"openai/gpt-5.2 + openai/gpt-5.4-mini + deterministic_fallback"},"name_source":"author_year","author_year":"Kragel2025"}}